Peter Drucker, father of the Knowledge Economy and business management guru said, “Knowledge has to be improved, challenged and increased constantly, or it vanishes.”

Nowadays, vanishing isn’t the worry. Rather, that knowledge – in the form of raw data – has been constantly and exponentially increasing. Data sources are myriad and everywhere.

Have a doctor’s appointment? Your vitals, diagnosis, and Rx get databased. Engage an e-commerce website? Your keystrokes and submitted information get funneled to a CRM. Run a factory? Smart machines record their performance metrics. Involved in a supply chain? Data on product distribution and raw material use gets monitored and stored for future reference.

With this ever-increasing aggregation of factual data, software platforms – many utilizing Online Analytical Processing (OLAP) technology – facilitate ad-hoc analysis across multiple dimensions. Once the data has been stored, BI software slices, dices, and juliennes it. Visualizations yield insight through charts and graphs that populate dashboards. Such business intelligence software delivers value by generating real-time analytics that delineate trends, from which company principals can confidently make proactive decisions rooted in facts.

Drucker would be thrilled with today’s Business Intelligence software, which by its very nature improves and challenges marketplace and workplace knowledge. He would find it unsurprising that the trend to use Business Intelligence software continues to surge.

The following infographic on 7 Key Trends reflects this sustained momentum, popularity, and utility of Business Intelligence software as we move toward 2019.

Keith Craig is Content Marketing Manager for Better Buys. He has more than a decade of experience using, researching and writing about business software and hardware. He can be found on Twitter and LinkedIn.

As the fields of business intelligence and business analytics continue to develop and grow, organizations must be aware of the distinctions between the terms and understand their value. Adoption and usage of business intelligence and analytics tools show no sign of slowing. Understanding these concepts is vital to making the best business decisions, to maintaining a competitive edge across all industries, and to enabling companies to capture operational and strategic value.

To learn more, see the infographic below created by Pepperdine University’s Online MBA program.

Distinguishing Business Analytics and Business Intelligence – Resource from Pepperdine University

Differences Between Business Analytics and Business Intelligence

The goal of business analytics is to develop successful analysis models. It simulates scenarios to predict future conditions. It is a very technical approach to predict upcoming trends. This process helps find patterns after analyzing previous and current data. The analysis is used to devise future courses of action. Professionals working in this field use data mining, descriptive modeling, and simulations.

Business intelligence uses different types of software applications to analyze raw data. Professionals working in this field study business information. They closely consult with decision-making managers. They identify existing business problems and analyze past and present data to determine performance quality. They use KPIs and other metrics, and prepare easy-to-read reports. The reports give unique insights into the workings of the business and empower organizations to make optimum business decisions.

Business analytics experts help predict what is going to happen in the future. They use data to analyze what will happen under certain specific conditions. They can predict the next trends and outcomes.

Business intelligence experts, on the other hand, help track and monitor data and business metrics. They can correctly identify what happened and what is happening now. They can discover why something happened, how many times something happened, and when all such events took place.

Data-Focused Talent Shortage

Very few managers have high expertise in data fields because the use and analysis of big data has emerged only in the last few years. Even new managers and leaders do not have requisite skills to devise data-driven digital strategies. Most organizations need a new kind of talent base that is well versed in the data-driven business landscape. One McKinsey report estimates that by 2018, the US will face a shortage of 140,000–190,000 data science professionals. Even now, companies must pay very high salaries to employ data analysts. Only large companies can afford such professionals.

The Future of Big Data Analytics

While 78% companies agree that big data will impact their business, only 58% think their company is ready to take advantage of all the potential that big data offers. The reason for this is not difficult to ascertain. Companies must use various techniques to capture data, and the data collected must be realized in a specific format. Data analysts must use exacting methods and processes to analyze this data. Capturing and analyzing big data is a complex process and can be handled only by trained data analysts.

Benefits of Business Analytics

Engaging effective business analytics is necessary to make the right business decisions. Managers with proven analytics skills are better able to plan for future projects. The biggest advantage involves forecasting. Analysis of previous and current data helps predict future trends. This information is crucial to the success of a business. A company may have different types of products. It may keep promoting the fast-selling product while another product that is quickly gaining traction may remain under the radar. Only big data analysis can reveal the importance of the latter product. Business analytics is a forward-thinking way to improve operational efficiency. Decisions can be made faster, and it becomes easier to make sense of large volumes of data.

Benefits of Business Intelligence

Business intelligence proves useful in identifying new opportunities. A company can identify a new market that holds important business opportunities. Product pricing can be tweaked to market demands. Business productivity can be improved. Sales and marketing expenses can be optimized. Business intelligence helps predict customer behavior, which proves useful in improving customer service.

Usage and Adoption of Big Data

Even when the benefits are well known, very few companies are able to use big data analysis in a significant way. Almost 50% of businesses face difficulty in the field of business analytics. They are unable to ensure the quality of data. Without the right talent to manage and analyze data, they are at a disadvantage in the market. Many businesses rely on simple applications to analyze data. These tools are not very effective in analyzing big data. This type of data must be analyzed scientifically. It is a complex job that can be handled only by professionals who possess training and skills in data analytics.

Developing a Big Data Analytics Culture

All types of businesses are working continuously to take advantage of big data. They are using simple as well as complex solutions to work with such data. There is a consensus realization that a high level of data analytics is necessary to ensure business success in today’s market. Now, companies are incorporating data analytics into all their departments. They are using sophisticated tools and solutions to predict future trends. Almost 82% of business executives now take advantage of data-driven reports and dashboards.

Sources of Big Data

Big data is obtained from a wide range of sources. Sales records and financial transactions generate a great volume of useful data. They help devise pricing models for different types of products. The customer database is a key source of data. Large amounts of contact details and other data can be mined from emails, productivity and communication applications. In fact, every business process generates data. All such data must be collected and stored properly.

Businesses need the services of both business analytics and business intelligence experts. There are differences in their positions, but both groups play important roles in the success of a business. As more and more businesses rely on digital strategies, they have to analyze their big data properly and effectively. They need the support of trained and skilled data analysts to help achieve the best business success possible.

Business Analytics vs. Data Science

“Business analytics” and “data science” — are they basically interchangeable terms, or entirely separate professional pursuits? There’s certainly overlap on the topic of Big Data and using data to inform decisions. There is no dispute over the fact that both business analysts and data scientists use exponentially growing sources of data to do their work. [Check out PARIS Tech’s recent post on Big Data]

An article and featured infographic by Angela Guess for Dataversity.net argues that the terms business intelligence and data scientist are distinct, and not just because one pursuit applies to business, and the other to scientific results.

Click below to read the original article which accompanies the business intelligence vs. data scientist infographic.

What is Business Analytics?

Science and business continue to intersect, most recently on the topic of data analytics. Generally speaking, “data analytics” is the process of organizing and interpreting data to uncover valuable information. “Business [data] analytics” is the more specific application of data analytics to business purposes.

Some examples of data analytics might be: What segment of customers use desktop v. mobile? Or, which target audience found value in the most recent advertising campaign? Companies ranging from Target to Google find results from these kinds of questions so valuable that they pay data analysts over $100,000 per year. To learn more about the burgeoning data analytics industry, check out this educational resource, created by Villanova University’s Master of Science in Analytics program.

Be Mindful to Keep these Practices throughout your Business Intelligence Project

Getting Business Intelligence Best Practices to work well is challenging. Check out the 6 best practices outlined in this Infographic. Check it out and see how your organization stacks up. It’s easy to think that bigger is better, or assume you need to start from scratch. Actually its about having BI policies in place, keeping everyone on the team involved, having a clear scope, and making sure everyone is trained up well.

It is also important for a Business Intelligence project to have an analytics model that reflects the organization.